Papers
Low-Rank Curvature for Zeroth-Order Optimization in LLM Fine-tuning
Hyunseok Seung, Jaewoo Lee, Hyunsuk Ko
A Solver-in-the-Loop Framework for Improving LLMs on Answer Set Programming for Logic Puzzle Solving
Timo Pierre Schrader, Lukas Lange, Tobias Kaminski et al.
Logical Characterizations of GNNs with Mean Aggregation
Moritz Schönherr, Carsten Lutz
Graph-Conditional Flow Matching for Relational Data Generation
Davide Scassola, Sebastiano Saccani, Luca Bortolussi
HN-MVTS: HyperNetwork-based Multivariate Time Series Forecasting
Andrey Savchenko, Oleg Kachan
DP-NCB: Privacy Preserving Fair Bandits
Dhruv Sarkar, Nishant Pandey, Sayak Ray Chowdhury
HyRNN: Hybrid Recurrent Neural Networks for Approximating Hybrid Dynamical Systems
Ricardo G. Sanfelice
Koopman Invariants as Drivers of Emergent Time-Series Clustering in Joint-Embedding Predictive Architectures
Pablo Ruiz-Morales, Dries Vanoost, Davy Pissoort et al.
Repetition Makes Perfect: Recurrent Graph Neural Networks Match Message Passing Limit
Eran Rosenbluth, Martin Grohe
A Differential Perspective on Distributional Reinforcement Learning
Juan Sebastian Rojas, Chi-Guhn Lee
A Unified Convergence Analysis for Semi-Decentralized Learning: Sampled-to-Sampled vs. Sampled-to-All Communication
Angelo Rodio, Giovanni Neglia, Zheng Chen et al.
GCL-OT: Graph Contrastive Learning with Optimal Transport for Heterophilic Text-Attributed Graphs
Yating Ren, Yikun Ban, Huobin Tan
BitDP: Ultra-low-bit Communication for Data Parallelism in LLM Training
Xiaozhe Ren, Qiong Luo
Discrete Structure Augmentation for Graph Convolutional Networks
Jianxin Ren, Weining Wu
LexInstructEval: Lexical Instruction Following Evaluation for Large Language Models
Huimin Ren, Yan Liang, Baiqiao Su et al.
TimeCAP: A Channel-Aware Pre-Training Framework for Multivariate Time Series Forecasting
Chuanru Ren, Yao Lu, Tianjin Huang et al.
ShapBPT: Image Feature Attributions Using Data-Aware Binary Partition Trees
Muhammad Rashid, Elvio G. Amparore, Enrico Ferrari et al.
Compensating Distribution Drifts in Continual Learning with Pre-trained Vision Transformers
Xuan Rao, Simian Xu, Zheng Li et al.
Catastrophic Forgetting in Kolmogorov-Arnold Networks
Mohammad Marufur Rahman, Guanchu Wang, Kaixiong Zhou et al.
On the Calibration of Image Semi-Supervised Learning Models
Mehrab Mustafy Rahman, Jayanth Mohan, Tiberiu Sosea et al.
QAPNet: A Quantum-Attentive Patchwise Network for Robust Medical Image Classification Under Noisy Inputs
Maqsudur Rahman, Jun Zhuang
PANDA – Patch and Distribution-Aware Augmentation for Long-Tailed Exemplar-Free Continual Learning
Siddeshwar Raghavan, Jiangpeng He, Fengqing Zhu
MoE^2: A Mixture-of-Mixtures of Experts for Ensemble-Free Domain Generalization
Ahmed Radwan, Mahmoud Soliman, Omar Abdelaziz et al.
Unsupervised Combinatorial Probabilistic Reasoning: Probabilistic Coin Change Problem
Zhongdi Qu, Yingheng Wang, Utku Umur Acikalin et al.
Exploiting Geometric Structures for Modeling Multi-Agent Behaviors: A New Thinking
Bohao Qu, Xiaofeng Cao, Bing Li et al.